Displaying 1 to 4 from 4 results

nlp - Selected Machine Learning algorithms for basic natural language processing in Golang

An implementation of selected machine learning algorithms for basic natural language processing in golang. The initial focus for this project is Latent Semantic Analysis to allow retrieval/searching, clustering and classification of text documents based upon semantic content.Built upon the gonum/gonum matrix library with some inspiration taken from Python's scikit-learn.

irlba - Fast truncated singular value decompositions

Implicitly-restarted Lanczos methods for fast truncated singular value decomposition of sparse and dense matrices (also referred to as partial SVD). IRLBA stands for Augmented, Implicitly Restarted Lanczos Bidiagonalization Algorithm. The package provides the following functions (see help on each for details and examples).Help documentation for each function includes extensive documentation and examples. Also see the package vignette, vignette("irlba", package="irlba").

imgsvd - Shiny Web Application for Image Compression via SVD

ImgSVD is a Shiny application for image compression via singular value decomposition (SVD). This application is inspired by Yihui Xie's comment in Yixuan Qiu's article on image compression via singular value decomposition with the R package rARPACK. Currently, ImgSVD supports input images in JPEG or PNG format.

rsparse - Fast and accurate machine learning on sparse matrices - Factorization Machines, FTRL, Matrix factorizations

rsparse is an R package for statistical learning on sparse data. Notably it implements many algorithms sparse matrix factorizations with a focus on applications for recommender systems. All of the algorithms benefit from OpenMP and most of them use BLAS. Package scales nicely to datasets with millions of rows and millions of columns.